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This small subproject regroup most of the stuff needed to build pmd. As some java code has been produced to reduce the use of scripts when generating the website, the build also requires a small jar, which is generated by this pom. IMPORTANT NOTE: the pmd-build.jar does not need to be recompile if you modify any ant or xslt files. You can alter the files that are in the xslt directory and directly uses the appropriate ant or java task. pmd-build should be recompiled and package (and its version incrememented) only if you modify the java code.

According to Docker best practices a Docker container should not be up if the process fails to load properly. Apache Tomcat deploys all the web applications loaded in its webapp folder. This is a resilient solution for web applications not influencing the application server. However, In a Docker environment according to best practice, the process should fail in case the web application failed to initialize properly. By adding the additional jar created by this project to Tomcat classpath and adding the new listener in the Tomcat conf/server.xml the user can make sure the Tomcat process fails in case there is an initialization exception in their web application which will cause the Tomcat used the tomcat container to abort in immediately indicate that there was an initialization error Abort tomcat when a webapp fails to deploy in Docker container Docker container best practice. Tomcat does not stop if a webapp fail to deploy and the container will continue to run. By adding this listener the tomcat will abort in case the Tomcat fails to deploy the webapp, And the container will not start. You will need to place the listener in Tomcat server.xml and set the Tomcat classpath to contain this jar

Some libraries from Matthew Johnson: http://www.matthew.ath.cx/projects/java/ Modifications: - including precompiled native C libraries (libunix-java) for architectures: arm, amd64 and i386 - UnixSocket/UnixServerSocket now implements closable (allows try-with-resources usage) - Cleaned up code style - Split test classes to test classpath - Introduced JUnit - Removed the whole CGI package, it should never ever been used these days

The crypto4j library provides a simple and pluggable crypto abstraction library for Java, including both cryptographic primitives and the artifacts defined in the JOSE standard. This library separates the cryptographic primitives from the JOSE artifacts. The library uses the algorithms available through JCA (JCE). The implementations of the cryptographic primitives provided in this library rely on the standard JCA implementation, and can be configured and extended through the JCA mechanisms. The JOSE portion of the library allows custom extensions by either replacing the provided JOSE artifact implementations with custom implementations, or by adding new JOSE artifacts, for instance in form of additional algorithms, which is particularly useful in case that the JOSE standard is updated or in case custom extensions to the JOSE standard should be implemented. The implementations available in this library generally come in two variants: a standard implementation of the primitives and advanced algorithms, and a high-performance implementation that takes advantage of implementation patterns that do not compromise cryprographic security, but speed up the overall processing time.

Bond is a small library that can be used to spy values and mock functions during tests. Spying is a replacement for writing the assertEquals in your test, which are tedious to write and even more tedious to update whem your test setup or code inevitably changes. With Bond, you separate what is being verified, e.g., the variable named output, from what value it should have. This way you can quickly spy several variables, even have structured values such as lists or dictionaries, and these values are saved into an observation log that is saved for future reference. If the test observations are different you have the option to interact with a console or visual tool to see what has changed, and whether the reference set of observations need to be updated.

This small subproject regroup most of the stuff needed to build pmd. As some java code has been produced to reduce the use of scripts when generating the website, the build also requires a small jar, which is generated by this pom. IMPORTANT NOTE: the pmd-build.jar does not need to be recompile if you modify any ant or xslt files. You can alter the files that are in the xslt directory and directly uses the appropriate ant or java task. pmd-build should be recompiled and package (and its version incrememented) only if you modify the java code.

Interactively classify through visual means. You are Presented with a scatter graph of the data against two user selectable attributes, as well as a view of the decision tree. You can create binary splits by creating polygons around data plotted on the scatter graph, as well as by allowing another classifier to take over at points in the decision tree should you see fit. For more information see: Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, Ian H. Witten (2001). Interactive machine learning: letting users build classifiers. Int. J. Hum.-Comput. Stud. 55(3):281-292.

Jadex XML is an XML data binding framework for Java and also for other representations. The main idea of Jadex XML is that neither the XML-Schema on the one side nor the Java classes on the other side should define the binding. Instead, a separate mapping between both is used as a mediation. This allows designing the XML representation independent of the Java side but still being able to connect both as desired. This idea was first put forward by the JiBX data binding framework. Jadex XML pushes it further by combining it with the configuration by exception principle. The framework can detect obvious correspondences between both sides automatically and only needs configuration information when translations are necessary. The configuration information is currently specified directly in form of Java configuration classes.

This metaclassifier makes its base classifier cost-sensitive using the method specified in Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive. In: Fifth International Conference on Knowledge Discovery and Data Mining, 155-164, 1999. This classifier should produce similar results to one created by passing the base learner to Bagging, which is in turn passed to a CostSensitiveClassifier operating on minimum expected cost. The difference is that MetaCost produces a single cost-sensitive classifier of the base learner, giving the benefits of fast classification and interpretable output (if the base learner itself is interpretable). This implementation uses all bagging iterations when reclassifying training data (the MetaCost paper reports a marginal improvement when only those iterations containing each training instance are used in reclassifying that instance).

This service implements the Indexer and Searcher interface of WebLab and connect to a remote SOLR engine in order to realize the functions. The connection is mandatory and thus the remote SOLR server should be started beforehand. Configuration of the SOLR server URL is found in src/main/webapp/WEB-INF/cxf-servlet.xml . See in particular "indexerServiceBean" and "searcherServiceBean". Moreover, the service implements several "Analyser" services that could be included in a complete search chain in order to: - enrich a ResultSet with metadata about Hits (see resultSetMetaEnricherServiceBean) - highlight snippet in ResultSet (see highlighterServiceBean) - provide facets related to the current results (see facetSuggestionServiceBean) - suggest spell correction of the original query (see spellSuggestionServiceBean)